MemoVision: a tool for feature selection and visualization of performance data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU149848" target="_blank" >RIV/00216305:26220/23:PU149848 - isvavai.cz</a>

Výsledek na webu

<a href="https://ismir2023program.ismir.net/lbd_322.html" target="_blank" >https://ismir2023program.ismir.net/lbd_322.html</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

MemoVision: a tool for feature selection and visualization of performance data

Popis výsledku v původním jazyce

Music performance analysis has traditionally been a peripheral topic in the music information retrieval community. However, it is sometimes included in the goals of music information retrieval studies—from low- and high-level parameter detection and synchronization methods to feature selection and measure transfer. In this contribution, we introduce the MemoVision software, which utilizes retrieval and feature selection methods for comparative music analysis. It is built with JavaScript and Python languages, combining the accessibility of a web-based interface and state-of-the-art feature extraction possibilities. Its features can be used separately or as a visualization tool for music performance case studies.

Název v anglickém jazyce

MemoVision: a tool for feature selection and visualization of performance data

Popis výsledku anglicky

Music performance analysis has traditionally been a peripheral topic in the music information retrieval community. However, it is sometimes included in the goals of music information retrieval studies—from low- and high-level parameter detection and synchronization methods to feature selection and measure transfer. In this contribution, we introduce the MemoVision software, which utilizes retrieval and feature selection methods for comparative music analysis. It is built with JavaScript and Python languages, combining the accessibility of a web-based interface and state-of-the-art feature extraction possibilities. Its features can be used separately or as a visualization tool for music performance case studies.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/TL05000527" target="_blank" >TL05000527: Paměť zvuku: evoluční principy interpretační tradice české hudby na příkladu děl Antonína Dvořáka a Bedřicha Smetany</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů